The disclosed embodiments relate generally to a system and method for improving the operability of a print production environment and, more particularly to an improved approach for forecasting print production demand in the print production environment.
Document production environments, such as print shops, convert printing orders, such as print jobs, into finished printed material. A print shop may process print jobs using resources such as printers, cutters, collators and other similar equipment. Typically, resources in print shops are organized such that when a print job arrives from a customer at a particular print shop, the print job can be processed by performing one or more production functions.
In one example of print shop operation, product variety (e.g., the requirements of a given job) can be low, and the associated steps for a significant number of jobs might consist of printing, inserting, sorting and shipping. In another example, product variety (corresponding, for instance, with job size) can be quite high and the equipment used to process these jobs (e.g. continuous feed machines and inserting equipment) can require a high changeover time. Experience working with some very large print shops has revealed that print demand exhibits a tremendous variety of time series behavior.
Forecasting demand for a given large print shop can be useful in, among other things, managing shop resources. However, traditional approaches of forecasting (as found in associated literature) may be insufficient to suitably forecast demand in large print shops with considerable print job variability. For instance, in literature relating to forecasting a preference toward using pooled demand forecast (as opposed to forecasting components individually and summing the forecasts to obtain an aggregate forecast) has been expressed. It has been found, however, that pooled demand forecasting can break down in, among other environments, print production environments when the job related demand exhibits relatively high levels of variability.
In U.S. patent application Ser. No. 11/868,993 to Rai et al. entitled System and Method of Forecasting Print Job Related Demand (filed on Oct. 9, 2007 and published on Apr. 9, 2009 as U.S. Patent Application Publication No. 2009/0094094-A1) demand data is collected for a print production environment and then segmented into a first demand series with at least two demand components and a second demand series with at least one demand component. The demand components are derived with a segmentation technique, which technique can be performed with a database attribute (e.g., an attribute, such as job or form type, client, duplex/simplex (i.e., media “plex”); obtained from a data warehouse, by time slice (e.g., Mondays or firsts of the month), or by statistical thresholding (e.g., demand over and under 30,000 prints). In practice a first demand related forecast is generated with a combination of the at least two demand components and a second demand related forecast may be generated with the at least one demand component. In one approach, the first and second demand related forecasts may be shown or used in an aggregate plot, the aggregate plot being used to obtain forecast demand data for the print production environment.
Forecasting with the disclosed approach of the '993 Patent Application is well suited for its intended purpose. In particular, use of the disclosed approach can clearly lead to significantly improved forecasting (i.e., reasonably low levels of mean absolute percentage error [MAPE]). Nonetheless, it is believed that the approach disclosed and claimed below may, under certain circumstances, result in even lower levels of MAPE.
In one aspect of the disclosed embodiments there is disclosed a print demand forecasting system for use with a print production system in which multiple print jobs are processed over a selected time interval. The print demand forecasting system includes: a data collection tool, said data collection tool collecting print demand data for each print job processed during the selected time interval; mass memory for storing the collected print demand data; a computer implemented service manager for processing the stored print demand data to obtain a first time series component and a second time series component, said computer implemented service corresponding the first time series component with a first forecast model and the second time series component with a second forecast model; and a selector process, operating with said computer implemented service manager to select one of the first forecast model and the second forecast model, the selected one of the first forecast model and the second forecast model being used to obtain forecast data for a selected time outside of the selected time interval.
In another aspect of the disclosed embodiments there is disclosed A print demand forecasting method for use with a print production system in which multiple print jobs are processed over a selected time interval. The print demand forecasting method includes: collecting print demand data for each print job processed during the selected time interval; storing the collected print demand data in memory; processing the stored print demand data to obtain a first time series component and a second time series component; corresponding the first time series component with a first forecast model and the second time series component with a second forecast model; selecting one of the first forecast model and the second forecast model; and using the selected one of the first forecast model and the second forecast model obtain forecast data for a selected time outside of the selected time interval.